public class MekaClassifierSplitEvaluator extends weka.experiment.ClassifierSplitEvaluator implements MekaSplitEvaluator
Valid options are:
-W <class name> The full class name of the classifier. eg: weka.classifiers.bayes.NaiveBayes
-C <index> The index of the class for which IR statistics are to be output. (default 1)
-I <index> The index of an attribute to output in the results. This attribute should identify an instance in order to know which instances are in the test set of a cross validation. if 0 no output (default 0).
-P Add target and prediction columns to the result for each fold.
-no-size Skips the determination of sizes (train/test/classifier) (default: sizes are determined)
Options specific to classifier weka.classifiers.rules.ZeroR:
-D If set, classifier is run in debug mode and may output additional info to the consoleAll options after -- will be passed to the classifier.
Constructor and Description |
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MekaClassifierSplitEvaluator()
No args constructor.
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Modifier and Type | Method and Description |
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java.lang.String |
classifierTipText()
Returns the tip text for this property
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java.lang.Object[] |
getKey()
Gets the key describing the current SplitEvaluator.
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java.lang.String[] |
getKeyNames()
Gets the names of each of the key columns produced for a single run.
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java.lang.Object[] |
getKeyTypes()
Gets the data types of each of the key columns produced for a single run.
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java.lang.Object[] |
getResult(weka.core.Instances train,
weka.core.Instances test)
Gets the results for the supplied train and test datasets.
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java.lang.String[] |
getResultNames()
Gets the names of each of the result columns produced for a single run.
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java.lang.Object[] |
getResultTypes()
Gets the data types of each of the result columns produced for a single
run.
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java.lang.String |
getRevision()
Returns the revision string.
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int |
getTotalNumClasses()
Returns the overal number of classes.
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java.lang.String |
globalInfo()
Returns a string describing this split evaluator
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void |
setClassifier(weka.classifiers.Classifier newClassifier)
Sets the classifier.
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void |
setTotalNumClasses(int value)
Sets the overal number of classes.
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enumerateMeasures, getAttributeID, getClassForIRStatistics, getClassifier, getMeasure, getNoSizeDetermination, getOptions, getPredTargetColumn, getRawResultOutput, listOptions, noSizeDeterminationTipText, setAdditionalMeasures, setAttributeID, setClassForIRStatistics, setClassifierName, setNoSizeDetermination, setOptions, setPredTargetColumn, toString
public MekaClassifierSplitEvaluator()
public void setTotalNumClasses(int value)
setTotalNumClasses
in interface MekaSplitEvaluator
value
- the number of classespublic int getTotalNumClasses()
getTotalNumClasses
in interface MekaSplitEvaluator
public java.lang.String globalInfo()
globalInfo
in class weka.experiment.ClassifierSplitEvaluator
public java.lang.Object[] getKeyTypes()
getKeyTypes
in interface weka.experiment.SplitEvaluator
getKeyTypes
in class weka.experiment.ClassifierSplitEvaluator
public java.lang.String[] getKeyNames()
getKeyNames
in interface weka.experiment.SplitEvaluator
getKeyNames
in class weka.experiment.ClassifierSplitEvaluator
public java.lang.Object[] getKey()
getKey
in interface weka.experiment.SplitEvaluator
getKey
in class weka.experiment.ClassifierSplitEvaluator
public java.lang.Object[] getResultTypes()
getResultTypes
in interface weka.experiment.SplitEvaluator
getResultTypes
in class weka.experiment.ClassifierSplitEvaluator
public java.lang.String[] getResultNames()
getResultNames
in interface weka.experiment.SplitEvaluator
getResultNames
in class weka.experiment.ClassifierSplitEvaluator
public java.lang.Object[] getResult(weka.core.Instances train, weka.core.Instances test) throws java.lang.Exception
getResult
in interface weka.experiment.SplitEvaluator
getResult
in class weka.experiment.ClassifierSplitEvaluator
train
- the training Instances.test
- the testing Instances.java.lang.Exception
- if a problem occurs while getting the resultspublic void setClassifier(weka.classifiers.Classifier newClassifier)
setClassifier
in class weka.experiment.ClassifierSplitEvaluator
newClassifier
- the new classifier to use.public java.lang.String classifierTipText()
classifierTipText
in class weka.experiment.ClassifierSplitEvaluator
public java.lang.String getRevision()
getRevision
in interface weka.core.RevisionHandler
getRevision
in class weka.experiment.ClassifierSplitEvaluator